The detection and classification of the mental state elicited by humor from EEG patterns

S Ramaraju; Mohammed Roula; A Izzidien

doi:10.1109/EMBC.2015.7318648

The detection and classification of the mental state elicited by humor from EEG patterns

S Ramaraju, Mohammed Roula, A Izzidien

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper we investigate the use of EEG to detect the affective state of humor. The EEG of five subjects was recorded while they recalled humorous videos. Extracted frequency features were compared to a control state in which users where asked to remain in a neutral mental state. An ANOVA test performed on the two groups: neutral and humor recall found a statistically significant difference in the frequency range 28-32 Hz for a number of channels including T7 and P7. Both of which presented the greatest statistically significant results with p values of 0.009 and 0.0 respectively Furthermore, we demonstrate that these mental states can be classified using Principal Component Analysis followed by a 3 features Linear Discriminant Analysis resulting in a leave one out classification accuracy of 95%.

Original language	English
Title of host publication	Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
Publisher	Institute of Electrical and Electronics Engineers
Pages	1472-1475
Number of pages	4
ISBN (Electronic)	978-1-4244-9271-8
ISBN (Print)	978-1-4244-9269-5
DOIs	https://doi.org/10.1109/EMBC.2015.7318648
Publication status	Published - 5 Nov 2015
Event	37th Annual Conference of the IEEE Engineering in Medicine and Biology Society (2015): Biomedical Engineering - a Bridge to improve the Quality of Health Care and the Quality of Life - MiCo - Milano Conference Center, Milan, Italy Duration: 25 Aug 2015 → 29 Aug 2015 http://embc.embs.org/2015/

Conference

Conference	37th Annual Conference of the IEEE Engineering in Medicine and Biology Society (2015)
Abbreviated title	EMBC 2015
Country/Territory	Italy
City	Milan
Period	25/08/15 → 29/08/15
Internet address	http://embc.embs.org/2015/

Keywords

electroencephalography
Temporal lobe
feature extraction
Analysis of Variance
Accuracy
Computers
Emotion recognition
signal classification
bioelectric potentials
medical disorders
medical signal detection
neurophysiology
principal component analysis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/EMBC.2015.7318648Licence: CC BY-NC-ND

Cite this

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title = "The detection and classification of the mental state elicited by humor from EEG patterns",

abstract = "In this paper we investigate the use of EEG to detect the affective state of humor. The EEG of five subjects was recorded while they recalled humorous videos. Extracted frequency features were compared to a control state in which users where asked to remain in a neutral mental state. An ANOVA test performed on the two groups: neutral and humor recall found a statistically significant difference in the frequency range 28-32 Hz for a number of channels including T7 and P7. Both of which presented the greatest statistically significant results with p values of 0.009 and 0.0 respectively Furthermore, we demonstrate that these mental states can be classified using Principal Component Analysis followed by a 3 features Linear Discriminant Analysis resulting in a leave one out classification accuracy of 95%.",

keywords = "electroencephalography, Temporal lobe, feature extraction, Analysis of Variance, Accuracy, Computers, Emotion recognition, signal classification, bioelectric potentials, medical disorders, medical signal detection, neurophysiology, principal component analysis",

author = "S Ramaraju and Mohammed Roula and A Izzidien",

year = "2015",

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doi = "10.1109/EMBC.2015.7318648",

language = "English",

isbn = "978-1-4244-9269-5",

pages = "1472--1475",

booktitle = "Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE",

publisher = "Institute of Electrical and Electronics Engineers",

note = "37th Annual Conference of the IEEE Engineering in Medicine and Biology Society (2015) : Biomedical Engineering - a Bridge to improve the Quality of Health Care and the Quality of Life, EMBC 2015 ; Conference date: 25-08-2015 Through 29-08-2015",

url = "http://embc.embs.org/2015/",

}

Ramaraju, S, Roula, M & Izzidien, A 2015, The detection and classification of the mental state elicited by humor from EEG patterns. in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. Institute of Electrical and Electronics Engineers, pp. 1472-1475, 37th Annual Conference of the IEEE Engineering in Medicine and Biology Society (2015), Milan, Italy, 25/08/15. https://doi.org/10.1109/EMBC.2015.7318648

The detection and classification of the mental state elicited by humor from EEG patterns. / Ramaraju, S; Roula, Mohammed; Izzidien, A.
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. Institute of Electrical and Electronics Engineers, 2015. p. 1472-1475.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - The detection and classification of the mental state elicited by humor from EEG patterns

AU - Ramaraju, S

AU - Roula, Mohammed

AU - Izzidien, A

PY - 2015/11/5

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N2 - In this paper we investigate the use of EEG to detect the affective state of humor. The EEG of five subjects was recorded while they recalled humorous videos. Extracted frequency features were compared to a control state in which users where asked to remain in a neutral mental state. An ANOVA test performed on the two groups: neutral and humor recall found a statistically significant difference in the frequency range 28-32 Hz for a number of channels including T7 and P7. Both of which presented the greatest statistically significant results with p values of 0.009 and 0.0 respectively Furthermore, we demonstrate that these mental states can be classified using Principal Component Analysis followed by a 3 features Linear Discriminant Analysis resulting in a leave one out classification accuracy of 95%.

AB - In this paper we investigate the use of EEG to detect the affective state of humor. The EEG of five subjects was recorded while they recalled humorous videos. Extracted frequency features were compared to a control state in which users where asked to remain in a neutral mental state. An ANOVA test performed on the two groups: neutral and humor recall found a statistically significant difference in the frequency range 28-32 Hz for a number of channels including T7 and P7. Both of which presented the greatest statistically significant results with p values of 0.009 and 0.0 respectively Furthermore, we demonstrate that these mental states can be classified using Principal Component Analysis followed by a 3 features Linear Discriminant Analysis resulting in a leave one out classification accuracy of 95%.

KW - electroencephalography

KW - Temporal lobe

KW - feature extraction

KW - Analysis of Variance

KW - Accuracy

KW - Computers

KW - Emotion recognition

KW - signal classification

KW - bioelectric potentials

KW - medical disorders

KW - medical signal detection

KW - neurophysiology

KW - principal component analysis

U2 - 10.1109/EMBC.2015.7318648

DO - 10.1109/EMBC.2015.7318648

M3 - Conference contribution

C2 - 26736548

SN - 978-1-4244-9269-5

SP - 1472

EP - 1475

BT - Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE

PB - Institute of Electrical and Electronics Engineers

T2 - 37th Annual Conference of the IEEE Engineering in Medicine and Biology Society (2015)

Y2 - 25 August 2015 through 29 August 2015

ER -

The detection and classification of the mental state elicited by humor from EEG patterns

Abstract

Conference

Keywords

UN SDGs

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Cite this